Aircraft intent processor

ABSTRACT

Example aircraft intent processors are described herein that can be used both for the prediction of an aircraft&#39;s trajectory from aircraft intent, and the execution of aircraft intent for controlling the aircraft. An example aircraft intent processor includes an aircraft intent input to receive aircraft intent data representative of aircraft intent instructions, an aircraft state input to receive state data representative of a state of the aircraft, and a residual output. The aircraft intent processor is to calculate residual data representative of an error between a state of the aircraft commanded by the received aircraft intent data and the state of the aircraft expressed by received state data, and output the residual data via the residual output.

RELATED APPLICATION

This patent claims priority to European Patent Application No.14382083.5, filed Mar. 7, 2014, and entitled “An Aircraft IntentProcessor,” which is hereby incorporated by reference in its entirety.

FIELD OF THE INVENTION

The present disclosure relates to a processor and, more particularly, toan aircraft intent processor that can be used both for the prediction ofan aircraft's trajectory from aircraft intent, and the execution ofaircraft intent for controlling the aircraft.

BACKGROUND

The ability to predict an aircraft's trajectory is useful for severalreasons.

Air traffic management (ATM) would benefit from an improved ability topredict an aircraft's trajectory. ATM is responsible for the safeseparation of aircraft, a particularly demanding task in congestedairspace such as around airports. ATM decision-support tools based onaccurate trajectory predictions could allow a greater volume of aircraftto be handled while maintaining safety. Trajectory is a four-dimensionaldescription of the aircraft's path. The description may be the evolutionof the aircraft's state with time, where the state may include theposition of the aircraft's center of mass and other aspects of theaircraft's motion such as velocity, attitude and weight. This benefit isparticularly significant where ATM is operating in and around airports.As demand for slots at airports increases, ATM is under constantpressure to increase capacity by decreasing separation between aircraft;increased accuracy in predicting aircraft trajectories enables this tobe done without compromising safety. Also, greater predictability inaircraft trajectories allows arrival times to be determined moreaccurately, thereby enabling better coordination with ground operations.

In current ATM practice, aircraft must typically fly set routes. Forexample, when approaching and departing an airport, aircraft are usuallyrequested to fly a Standard Terminal Arrival Route (STAR) and a StandardInstrument Departure (SID), respectively. However, aircraft operatorsare increasingly requesting additional flexibility to fly according totheir preferences, so that they can better pursue their businessobjectives. Furthermore, there is an increasing pressure on the ATMsystem to facilitate the reduction of the environmental impact ofaircraft operations. As a result of the above, the ATM system requiresthe capability to predict operator-preferred trajectories as well astrajectories that minimize the impact on the environment, particularlyin terms of noise and emissions. In addition, the ATM system must beable to exchange descriptions of such trajectories with the operators inorder to arrive at a coordinated, conflict-free solution to the trafficproblem.

The ability to predict an aircraft's trajectory would also be beneficialto the management of autonomous vehicles such as unmanned air vehicles(UAVs), for example in programming flight plans for UAVs as well as incommanding and de-conflicting their trajectories.

International PCT Patent Publication WO2009/042405 describes the generalconcepts of aircraft intent and flight intent, and thecomputer-implemented application of those concepts in formal languages,referred to as the aircraft intent description language (AIDL) and theflight intent description language. WO2009/042405 is hereby incorporatedby reference in its entirety.

European Patent Application EP2482269, which is also in the name of TheBoeing Company, describes flight intent in more detail. EP2482269 ishereby incorporated by reference in its entirety.

SUMMARY

An aircraft intent processor is disclosed herein. In some examples, theprocessor can calculate residual data representative of error in a stateof an aircraft (e.g., location, speed, and attitude) as compared withthat instructed by aircraft intent instructions.

Such processors can advantageously be used in both flight controlsystems for controlling aircraft, and also in air traffic controlsystems for monitoring aircraft, which results in better correspondencebetween actual trajectory achieved by an aircraft following the aircraftintent instructions and prediction of an aircraft's trajectory by airtraffic control using the same aircraft intent instructions.

An example apparatus disclosed herein includes an aircraft intentprocessor having an aircraft intent input to receive aircraft intentdata representative of aircraft intent instructions, an aircraft stateinput to receive state data representative of a state of an aircraft,and a residual output. The aircraft intent processor is to calculateresidual data representative of an error between a state of the aircraftcommanded by the aircraft intent data and the state of the aircraftexpressed by the state data and output the residual data via theresidual output.

An example system disclosed herein includes an aircraft having anactuator and a first aircraft intent processor and an air trafficcontrol station to monitor the aircraft. The air traffic control stationhas a second aircraft intent processor. Aircraft intent datarepresentative of aircraft intent instructions is received by theaircraft and the air traffic control station. The aircraft is to executethe aircraft intent instructions using the first aircraft intentprocessor. In the example system, the first aircraft intent processorincludes a first aircraft intent input to receive the aircraft intentdata, a first aircraft state input to receive first state datarepresentative of a first state of the aircraft, and a first residualoutput. The first aircraft intent processor is to calculate firstresidual data representative of a first error between a state of theaircraft commanded by the received aircraft intent data and the firststate of the aircraft expressed by the first state data and output thefirst residual data via the first residual output. In the examplesystem, the air traffic control station is to predict the trajectory ofthe aircraft using the second aircraft intent processor.

Disclosed herein is an example method of controlling an aircraft orpredicting a trajectory of the aircraft using an aircraft intentprocessor that includes an aircraft intent input, an aircraft stateinput, and a residual output. The example method includes receiving,with the aircraft intent input, aircraft intent data representative ofaircraft intent instructions, receiving, with the aircraft state input,state data representative of a state of the aircraft, calculatingresidual data representative of an error between a state of the aircraftcommanded by the received aircraft intent data and the state of theaircraft expressed by the received state data, and outputting theresidual data via the residual output.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a set of example instructions that may be used todescribe aircraft intent.

FIG. 2 illustrates an example schematic representation of an aircrafthaving an example flight control system.

FIG. 3 illustrates an example schematic representation of an air trafficcontrol system having an example trajectory computation infrastructure.

FIG. 4 illustrates the example flight control system of FIG. 2 forcontrolling an aircraft.

FIG. 5 illustrates the example trajectory computation infrastructure formonitoring aircraft.

FIG. 6 is a flow chart representative of an example method ofcontrolling an aircraft that may be implemented by the example flightcontrol system of FIG. 4.

FIG. 7 is a flow chart of an example method of computing the trajectoryof an aircraft that may be implemented by the example trajectorycomputation infrastructure of FIG. 5.

DETAILED DESCRIPTION

Before describing the details of the present disclosure, a briefoverview of the concept of aircraft intent is provided. Aircraft intentis a description of how an aircraft is to be flown during a timeinterval. Aircraft intent includes a set of instructions havingconfiguration instructions that describe the aerodynamic configurationof the aircraft (e.g., the positioning of flaps, slats, rudders and/orelevators) and motion instructions that describe the motion of theaircraft (e.g., in terms of speeds and accelerations).

The aircraft intent instructions must comply with a set of rules toensure that the configuration instructions correctly define theaerodynamic configuration of the aircraft and that the motioninstructions close the degrees of freedom of equations of motion used todescribe the aircraft motion.

International PCT Patent Publication WO2009/042405 describes anexpression of a set of aircraft intent instructions in a formallanguage, aircraft intent description language (AIDL), which defines thetrajectory of the aircraft. This expression is used by the trajectorycomputation engine to solve the equations of motion that govern theaircraft's motion.

There are many different sets of equations of motion that describe anaircraft's motion known to those of ordinary skill in the art. The setsof equations generally differ due to their complexity. In principle, anyof these sets of equations may be used. The actual form of the equationsof motion influences how the AIDL should be formulated because variablesthat appear in the equations of motion also appear in the instructionsdefining the aircraft intent.

The set of equations of motion may describe the motion of the aircraft'scenter of gravity, with the aircraft considered as a mass-varying rigidsolid. Three coordinates may describe the position of the aircraft'scenter of mass (longitude, latitude and altitude) and three values maydescribe the aircraft's attitude (roll, pitch and yaw). To derive theequations, a set of simplifying assumptions may be applied to thegeneral equations describing atmospheric, powered flight.

The equations of motion include variables relating to the aircraft'sperformance and meteorological conditions, and these are provided by theaircraft performance model and an earth model. To solve the equations,the configuration of the aircraft must be specified. For example,information may be required to resolve the settings of the landing gear,speed brakes and high lift devices.

International PCT Patent Publication WO2009/042405 describes usingequations of motion that form a system of seven non-linear ordinarydifferential equations, along with a definition of a given aircraftconfiguration comprising landing gear setting, high-lift devicessettings and speed brakes setting, that have one independent variable(time), ten dependent variables and hence three mathematical degrees offreedom (i.e., the number of dependent variables less the number ofequations). Thus, this choice of the equations of motion means that itis necessary to define externally the three degrees of freedom to obtaina closed solution thereby defining the aircraft trajectoryunambiguously, plus three further degrees of freedom to define theaircraft's configuration (the landing gear, speed brakes and high-liftdevices inputs must be closed at any time to obtain the trajectory).

The AIDL is a formal language whose primitives are the instructions. Thegrammar of the formal language provides the framework that allowsinstructions to be combined into sentences that describe operations.Each operation contains a complete set of instructions that close therequired six degrees of freedom in the equations of motion and sounambiguously defines the aircraft trajectory over its associatedoperation interval.

Instructions may be thought of as indivisible pieces of information thatcapture basic commands, guidance modes and control inputs at thedisposal of the pilot and/or the flight management system. Eachinstruction may be characterised by three main features: the effect ofan instruction; the meaning of an instruction; and the executioninterval.

The effect of an instruction is defined by a mathematical description ofthe instruction's influence on the aircraft's motion. The instruction isexpressed as a mathematical equation that must be fulfilled along withthe equations of motion during the instruction's execution interval.

The meaning of an instruction is given by the instruction's intrinsicpurpose and is related to the operational purpose of the command,guidance mode or control input captured by the instruction.

The execution interval is the period during which the instruction isaffecting the aircraft's motion (i.e., the time during which theequations of motion and the instruction's effect must be simultaneouslysatisfied). In some examples, the execution of different instructionsmay overlap, and such instructions are said to be compatible. In someexamples, other instructions are incompatible, and so cannot haveoverlapping execution intervals (e.g., instructions that cause aconflicting requirement for the aircraft to ascend and descend).

The instructions are divided into groups, with the division primarilyfocussing on the effect of the instructions, and then on groupingincompatible instructions together, as illustrated in FIG. 1. At a toplevel, the instructions are divided into two groups: configurationinstructions 270; and motion instructions 260.

Configuration instructions 270 relate to the aircraft's instantaneousaerodynamic configuration as determined by the high-lift devices,landing gear and speed brakes. The effect of any member of this group isthe time evolution of the position of the associated components.

The first group (Group No. 11) of the configuration instructions 270 isthe high lift configuration (HLC), and includes the instructions sethigh-lift devices (SHL) (Instruction No. 24), high-lift devices law(HLL) (Instruction No. 25) and hold high-lift devices (HHL) (InstructionNo. 26).

The second group (Group No. 12) of the configuration instructions 270 isthe speed brakes configuration (SBC), and includes the instructions setspeed brakes (SSB) (Instruction No. 27), speed brakes law (SBL)(Instruction No. 28) and hold speed brakes (HSB) (Instruction No. 29).

The third group (Group No. 13) of the configuration instructions 270 isthe landing gear configuration (LGC), and includes the instructions setopen loop speed brakes (OLSB) (Instruction No. 30), landing gear (SLG)(Instruction No. 31) and hold landing gear (HLG) (Instruction No. 32).

As the configuration of the aircraft must be fully determined at alltimes, there must always be an active instruction from each of thesegroups (Group Nos. 11-13) of the configuration instructions 270.

The motion instructions 260 capture the flight control commands,guidance modes and navigation strategies that may be employed. Theeffect of a motion instruction is defined as a mathematical equationthat unambiguously determines one of the degrees of freedom during theexecution interval of the instruction. At any one instant, three motioninstructions must be active to close the three degrees of freedom.

The motion instructions are classified into ten groups (Group Nos. 1-10)according to their effect, each group containing incompatibleinstructions as follows.

-   1. Speed guidance (SG) (Group No. 1).    -   Includes speed law (SL) (Instruction No. 1) and hold speed (HS)        (Instruction No. 2).-   2. Horizontal speed guidance (HSG) (Group No. 2).    -   Includes horizontal speed law (HSL) (Instruction No. 3) and hold        horizontal speed (HHS) (Instruction No. 4).-   3. Vertical speed guidance (VSG) (Group No. 3).    -   Includes vertical speed law (VSL) (Instruction No. 5) and hold        vertical speed (HVS) (Instruction No. 6).-   4. Path angle guidance (PAG) (Group No. 4).    -   Includes set path angle (SPA) (Instruction No. 7), path angle        law (PAL) (Instruction No. 8) and hold path angle (HPA)        (Instruction No. 9).-   5. Local altitude guidance (LAG) (Group No. 5).    -   Includes altitude law (AL) (Instruction No. 10) and hold        altitude (HA) (Instruction No. 11).-   6. Vertical positional guidance (VPG) (Group No. 6).    -   Includes track vertical path (TVP) (Instruction No. 12).-   7. Throttle control (TC) (Group No. 7).    -   Includes set throttle (ST) (Instruction No. 13), throttle law        (TL) (Instruction No. 14), hold throttle (HT) (Instruction        No. 15) and open loop throttle (OLT) (Instruction No. 16).-   8. Lateral directional control (LDC) (Group No. 8).    -   Includes set bank angle (SBA) (Instruction No. 19), bank angle        law (BAL) (Instruction No. 20), hold bank angle (HBA)        (Instruction No. 21) and open loop bank angle (OLBA)        (Instruction No. 22).-   9. Directional guidance (DG) (Group No. 9).    -   Includes course law (CL) (Instruction No. 17) and hold course        (HC) (Instruction No. 18).-   10. Lateral positional guidance (LPG) (Group No. 10).    -   Includes track horizontal path (THP) (Instruction No. 23).

The information received relating to the aircraft intent (e.g., flightintent, operator preferences, pilot selections, flying procedures, etc.)may be mapped to the instructions in the groups above. For example, amanual input throttle control maps to the TC group (Group No. 7).Similarly, a pilot may select a climb-out procedure that contains bothspeed and flight path angle, thereby mapping to the VSG and PAG groups(Group Nos. 3 and 4), along with a bearing to maintain that maps to theLPG group (Group No. 10).

Seven rules govern the possible combinations of instructions, asfollows.

-   1. An operation must have six instructions (follows from 3 and 4    below).-   2. Each instruction must come from a different group (as members of    the same group are incompatible).-   3. One instruction must come from each of HLC, LGC and SBC (i.e.,    the configuration instruction groups, to define the configuration of    the aircraft).-   4. Three instructions must come from the following groups: DG, LPG,    LDC, TC, SG, HSG, VSG, PAG, LAG and VPG (i.e., the motion    instruction groups to close the three degrees of freedom).-   5. One and only one instruction must come from DG, LPG and LDC    (e.g., to avoid conflicting requirements for lateral motion).-   6. Instructions from groups SG and HSG cannot be present    simultaneously (e.g., to avoid conflicting requirements for speed).-   7. Instructions from groups VSG, PAG, LAG and VPG cannot be present    simultaneously (e.g., to avoid conflicting requirements for vertical    speed, path angle and altitude).

The above lexical rules capture all the possible ways of unambiguouslydefining the aircraft trajectory prior to computing the trajectory.Consequently, an instance of aircraft intent that complies with theabove rules contains sufficient necessary information to compute aunique aircraft trajectory.

Each aircraft intent instruction has an associated instruction interval.A pair of triggers control the start and finish of each instructioninterval. These triggers may take different forms. For example, explicittriggers are divided into fixed and floating triggers. Implicittriggers, for example, are divided into linked, auto and defaulttriggers.

Starting with the explicit triggers, a fixed trigger refers to aspecified time instant for starting or ending an execution interval. Forexample, a pilot's decision to extend an aircraft's high lift devices ata particular time would be modelled as a set high lift devicesinstruction whose initial trigger condition would be fixed.

A floating trigger depends upon an aircraft state variable such as speedor altitude reaching a certain value to cause an execution interval tostart or end. Similarly, the trigger may be prompted by a mathematicalcombination of state variables meeting a certain condition. An examplewould be a set throttle to a specific engine regime that would beinvoked upon a certain speed being reached.

Turning now to implicit triggers, a linked trigger is specified inanother instruction. In this way, a series of triggers may create alogically ordered sequence of instructions where the chain of starttriggers is dependent upon the end trigger of the previous instruction.As such, a linked trigger points to an instruction rather than to acondition. Following on from the previous example of a set throttle to acertain regime triggered when a speed is reached, the subsequentinstruction may be a hold throttle to the engine regime achieved and alinked trigger would start this instruction.

Auto triggers delegate responsibility for determining whether theconditions have been met to the trajectory computation engine using theaircraft intent description. Such an arrangement is needed when theconditions are not known at the intent generation time, and only becomeapparent at the trajectory computation time. An example is an aircrafttracking a VHF omnidirectional range (VOR) radial whose intent is toperform a fly-by at a constant bank angle so as to intercept another VORradial. At the time of intent generation, there is no information onwhen to begin the turn. Instead, the information is computed by thetrajectory computation engine (e.g., by iterating on different solutionsto the problem). Hence the instruction set bank angle would have an autotrigger.

Default triggers represent conditions that are not known at intentgeneration, but are determined at trajectory computation because theconditions rely upon reference to the aircraft performance model. Theabove example of a set bank angle instruction had an auto start trigger,and will have a default end trigger that will be determined by the lawthat defines the time evolution of the aircraft's bank angle provided bythe aircraft performance model.

Aircraft intent may be used to control an aircraft and/or to predict theaircraft's trajectory. An example system disclosed herein includes anaircraft that is flown using aircraft intent and an air traffic controlsystem that predicts the aircraft's behaviour using (e.g., based on)aircraft intent.

An example aircraft 100 is illustrated in FIG. 2. In the illustratedexample, the aircraft 100 includes aircraft sensors 110, a navigationsystem 120, a flight control system 130, aircraft actuators 140 and amemory 150. The aircraft 100 may be, for example, an airliner with anautopilot facility or an unmanned aerial vehicle (UAV).

In the illustrated example, the aircraft sensors 110 provide datarelating to the position and attitude of the aircraft 100. The aircraftsensors 110 may include one or more of an altimeter, a pilot sensor, aGlobal Positioning System (GPS) receiver, a gyroscope, etc.

In the illustrated example, the navigation system 120 processes the dataprovided by the aircraft sensors 110 to determine the state of theaircraft 100 in terms of position and attitude to define the six degreesof freedom of the aircraft 100 (i.e., latitude, longitude, altitude,pitch, roll, and yaw). The navigation system 120 provides dataindicative of the state of the aircraft to the flight control system130. In the illustrated example, the memory 150 is configured to storeaircraft intent instructions.

In the illustrated example, the aircraft actuators 140 control theflight of the aircraft 100. For example, the aircraft actuators 140 maycontrol the deployment of the flaps and slats on the wings of theaircraft 100, the angle of the rudders and elevators on the empennageand/or the amount of thrust provided by the engines.

In the illustrated example, the flight control system 130 receivesaircraft intent instructions from the memory 150 and state data from thenavigation system 120. The flight control system 130 outputs controlsignals to the aircraft actuators 140 to control the aircraft 100 tocarry out the aircraft intent instructions.

An example air traffic control system 200 is illustrated in FIG. 3. Inthe illustrated example, the air traffic control system 200 includes airtraffic sensors 210, a tracking system 220, a trajectory computationinfrastructure 230, and a memory 250.

In the illustrated example, the air traffic sensors 210 sense theposition of one or more aircraft, such as the aircraft 100 of FIG. 2, ina predefined airspace. In some examples, the air traffic sensors 210also measure the speed of the aircraft 100. Additionally oralternatively, the speed may be derived from the rate of change ofmeasured position. The air traffic sensors 210 may include ground-basedradar, etc.

In the illustrated example, the tracking system 220 tracks one or moreaircraft, such as the aircraft 100 of FIG. 2, using data received fromthe air traffic sensors 210. The memory 250 is configured to storeaircraft intent instructions.

In the illustrated example, the trajectory computation infrastructure230 receives data on an aircraft's present location from the trackingsystem 220 and aircraft intent instructions from the memory 250, anduses the present location data and the aircraft intent instructions topredict the future trajectory of the aircraft 100.

In some examples, the future trajectory is output to a display 240.Additionally or alternatively, the predicted trajectory may be used in aconflict prediction method, which compares the predicted trajectoriesfor a plurality of aircraft to determine the potential for futurecollisions. If any potential future collisions are detected, then awarning may be displayed or communicated to the aircraft, and/orappropriate redirecting of aircraft may follow.

In some examples, the processes of using the flight control system 130to determine the correct actuator commands to carry out aircraft intentinstructions, and using the trajectory computation infrastructure 230 topredict future aircraft trajectory is carried out using a single coreprocess. The process, for example, includes the calculation of aresidual representing the difference between the aircraft's measured orpredicted state and the intended state dictated by the aircraft intentinstructions (e.g., the residual may be a vector of residuals for eachparameter of the state).

In the case of prediction using the trajectory computationinfrastructure 230, the residual represents the difference between theaircraft state predicted by the numerical modelling of the flight of theaircraft and the intended state dictated by the aircraft intentinstructions.

In the case of determining actuator commands using the flight controlsystem 130, the residual may represent the difference between theaircraft state measured by the navigation system 120 and the intendedstate dictated by the aircraft intent instructions.

Each of the motion instructions 260 of FIG. 1 has an associatedmathematical representation. For example, one of the aircraft intentinstructions is Hold Altitude (HA) (Instruction No. 11). This may berepresented as the difference between current altitude and the altitudewhen the instruction became/becomes active. This difference is anappropriate residual for the HA instruction. In some examples, theresidual is a vector having a residual value for each instruction.

The example flight control system 130 is illustrated in FIG. 4. In theillustrated example, the flight control system 130 has an aircraftintent processor 300 and a controller 135. The processor 300 may beimplemented as an Aircraft Intent Description Language (AIDL) processor.The controller 135 may be any form of control system, such as aproportional-integral-differential (PID) or proportional-differential(PD) controller.

In the illustrated example of FIG. 4, the aircraft intent processor 300includes an aircraft intent input 302, an aircraft state input 304, anda residual output 306. The aircraft intent input 302 receives aircraftintent data representative of aircraft intent instructions. In theaircraft 100 of FIG. 2, the aircraft intent data is provided by thememory 150. The aircraft state input 304 receives state datarepresenting the state of an aircraft. In the aircraft 100, this data isprovided by the navigation system 120.

In the illustrated example, the processor 300 compares the state datawith the aircraft intent data to determine the residual. The residualoutput 306 provides a signal to the controller 135. The controller 135implements a control system to control the aircraft actuators 140 tominimise the residual.

In the illustrated example, the aircraft intent processor 300 includesan AIDL decoder 310, a trigger manager 320, and an effect manager 330.These components have the same functionality whether they form part ofthe flight control system 130 or the trajectory computationinfrastructure 230.

In the illustrated example, the AIDL decoder 310 receives aircraftintent data from the aircraft intent input 302 and processes (e.g.,converts) the intent data to a form that can be executed by the effectmanager 330. In some examples, the AIDL decoder 310 is arranged tovalidate the received aircraft intent data. This may be achieved, forexample, by checking that the aircraft intent data complies with a setof rules, such as the seven rules described above.

In the illustrated example, the trigger manager 320 receives state datafrom the aircraft state input 304 and processes the received state datato determine when the triggers encoded in one or more of the aircraftintent instructions have been achieved. The effect manager 330 applieserror metrics to determine the residual to be output by the processor300 via the residual output 306. For example, in a scenario where eachaircraft intent instruction has associated therewith a mathematicalrepresentation, the error metrics may be used in the effects manager 330to calculate the residual for each instruction. The residual output 306may be a vector of values indicating the residual for each instruction.

The example trajectory computation infrastructure 230 is illustrated inFIG. 5. In the illustrated example, the trajectory computationinfrastructure 230 includes the aircraft intent processor 300 and anumerical solver 235.

In the illustrated example, the aircraft intent processor 300 is thesame as that employed in the flight control system 130, as illustratedin FIG. 4. The aircraft intent input 302 receives aircraft intent datarepresentative of aircraft intent instructions. In the air trafficcontrol system 200 of FIG. 3, the aircraft intent data is provided bythe memory 250. The aircraft state input 304 receives state datarepresenting the state of an aircraft. In the air traffic control system200, the state data is provided by the numerical solver 235.

In the illustrated example, the processor 300 compares the state datawith the aircraft intent data to determine the residual. The residualoutput 306 provides a signal to the numerical solver 235. The numericalsolver 235 evaluates the equations of motion for the aircraft 100 usingthe Earth model and aircraft performance model described herein. Thenumerical solver 235 predicts the behaviour of the aircraft 100 usinginputs of both the aircraft intent description described above and alsothe most recent known state of the aircraft provided by the trackingsystem 220. The numerical solver 235 provides as an output a predictionof the aircraft state following the execution of the received aircraftintent instructions given the most recently known state.

The aircraft performance model provides the values of the aircraftperformance aspects required by the numerical solver 235 to integratethe equations of motion. These values depend on the aircraft type forwhich the trajectory is being computed, the aircraft's current motionstate (e.g., position, velocity, weight, etc.) and/or the current localatmospheric conditions. In addition, the performance values may dependon the intended operation of the aircraft, i.e. on the aircraft intent.For example, the numerical solver 235 may use the aircraft performancemodel to provide a value of the instantaneous rate of descentcorresponding to a certain aircraft weight, atmospheric conditions(e.g., pressure, altitude and temperature) and intended speed schedule(e.g., constant calibrated airspeed). The numerical solver 235 may alsorequest from the aircraft performance model the values of the applicablelimitations to ensure that the aircraft motion remains within the flightenvelope. The aircraft performance model is also responsible forproviding the numerical solver 235 with other performance-relatedaspects that are intrinsic to the aircraft, such as flap and landinggear deployment times.

The Earth model provides information relating to environmentalconditions, such as the state of the atmosphere, weather conditions,gravity and magnetic variation. The numerical solver 235 uses theinputs, the aircraft performance model and the Earth model to solve theset of equations of motion. Many different sets of equations of motionare available that vary in complexity, and which may reduce theaircraft's motion to fewer degrees of freedom by means of a certain setof simplifying assumptions.

FIG. 6 illustrates a flow chart representative of an example method 600of controlling an aircraft using the flight control system 130 of FIG.4. The flight control system 130 may form part of the aircraft 100 ofFIG. 2.

In the illustrated example, the AIDL decoder 310 receives aircraftintent data and decodes it into the correct form. The AIDL decoder 310receives aircraft intent data (block 310-1). In some examples, theaircraft intent data is received in a serialised form and stored by theAIDL decoder 310. In the illustrated example, the AIDL decoder 310parses the received and stored aircraft intent data to identify the AIDLinstructions (block 310-2) and decodes the parsed AIDL instructions(block 310-3). In some examples, the AIDL decoder 310 checks or verifiesthat the AIDL instructions are valid (block 310-4) (e.g., by checkingthat the instructions comply with the seven rules described above). Ifthere is an error in the AIDL instructions (e.g., as determined at block310-4), the AIDL decoder 310 may flag that there is an error (block310-6). If the AIDL instructions are valid (e.g., as determined at block310-4), the AIDL decoder 310 creates an AIDL intent object (block310-5), which represents all of the aircraft intent instructions encodedin the received aircraft intent data.

In the illustrated example, once the AIDL decoder 310 has decoded theaircraft intent data into the correct form, the AIDL decoder 310notifies the controller 135 that the aircraft intent is ready forexecution (block 135-1). The controller 135 waits for a command signalto commence execution of the aircraft intent instructions (block 135-2).Once a command is received by the controller 135 (block 135-3), thecontroller awaits aircraft state data from the aircraft state input 406(block 135-4).

In the illustrated example, the navigation system 120 communicatesaircraft state data to the aircraft state input 304, and the aircraftstate input 304 provides this data to the controller 135 (block 135-5).The aircraft state data is sent to the trigger manager 320. In theillustrated example, the trigger manager 320 evaluates whether one ormore of the trigger conditions associated with the presently activeaircraft intent instruction has been achieved (block 320-1).

Initially, the active aircraft intent instructions are the firstinstructions in the AIDL object (e.g., the set of the first instructionsthat close all of the degrees of freedom of the aircraft 100 of FIG. 2).As the trigger conditions are met, the subsequent instructions becomevalid in order.

In the illustrated example, if any one of the trigger conditions is met,the active aircraft intent instructions are updated (block 320-2). Forexample, this could mean that the aircraft intent instruction for one ofthe configurations or motions is replaced with the next instruction forthat configuration or motion.

In the illustrated example, if there are further instructions available,the method 600 proceeds to the effect manager 330. Otherwise, allavailable aircraft intent instructions have been completed (block320-3).

In the illustrated example, if none of the trigger conditions have beenachieved, the example method 600 proceeds directly to the effect manager330. The effect manager 330 evaluates the effect of the aircraft intentinstruction (block 330-1). In some examples, each aircraft intentinstruction has associated therewith an error metric, which may be usedto calculate a residual. The residual indicates how closely the aircraftstate matches that instructed by the aircraft intent instructions. Insome examples, the effect manager 330 evaluates the residual using theerror metric associated with the instruction and the aircraft statevector.

In the illustrated example, the residuals are available for use byanother component of the system (block 330-2). The example method 600moves back to the controller 135. The controller 135 computes theappropriate actuator commands (block 135-6) to reduce the residual madeavailable at block 330-2. The actuator commands may be used to actuatethe actuators 140 of the aircraft 100 of FIG. 2.

FIG. 7 illustrates a flow chart representative of an example method 700of computing the trajectory of an aircraft using the trajectorycomputation infrastructure 230 of FIG. 5. The trajectory computationinfrastructure 230 may form part of the air traffic control system 200of FIG. 3.

In the illustrated example, the portions of the method 700 carried outby the AIDL decoder 310, the trigger manager 320 and the effect manager330 are substantially the same as in the example method 600 of FIG. 6.The difference between the method 600 and the method 700 is the actionof the numerical solver 235 instead of the controller 135.

In the illustrated example of FIG. 7, blocks 310-1 through 310-6 are thesame as in the example method 600 of FIG. 6 and provide the aircraftintent instructions.

In the illustrated example, once the AIDL decoder 310 has decoded theaircraft intent data into the correct form, the AIDL decoder 310 maynotify the numerical solver 235 that the aircraft intent is ready forexecution (block 235-1). The numerical solver 235 waits for a commandsignal to commence computation of the aircraft trajectory based on theaircraft intent instructions (block 235-2). The numerical solver 235awaits the initial conditions from which the aircraft trajectory will bederived (block 235-3). The initial conditions may be provided, forexample, by the air traffic sensors 210 of FIG. 3.

In the illustrated example, the numerical solver 235 evaluates theequations of motion using the aircraft state and the presently activeaircraft intent instruction (block 235-4). This step results in thecomputation of errors indicating how well the aircraft state fits theequations of motion.

Initially, the aircraft state is defined by the initial conditions.Subsequently, the method 700 proceeds iteratively by evaluating theequations of motion using the predicted aircraft state.

The operations at blocks 330-1 and 330-2 are performed the same as inFIG. 6 and are implemented by the processor 300 to determine theresiduals based on the aircraft state and the active aircraft intentinstruction.

Using the residuals, the numerical solver 235 determines whether thepredicted aircraft state is a valid solution to the equations of motion(block 235-5) using the calculated errors from block 235-4 of how wellthe aircraft state fits the equations of motion, the calculatedresiduals from block 330-1 and the aircraft intent instruction. Forexample, the set of errors (from block 235-4) and residuals (from block330-1) can be compared with a set of corresponding thresholds such thatthe predicted aircraft state is found to be a valid solution if everyerror is less than its corresponding threshold.

In the illustrated example, if the predicted state is determined to benot valid (block 235-5), a new estimate is generated (block 235-6). Insome examples, the new estimate may be generated by making a smallrandom adjustment to the predicted state found to be invalid.

In the illustrated example, if the predicted state is determined to bevalid (block 235-5), then the trigger manager 320 is used to implementmethod at blocks 320-1 and 320-2, which are performed the same as inFIG. 6, =to establish whether any of the trigger conditions associatedwith the active aircraft intent instruction has been achieved and toupdate the active aircraft intent instruction if necessary.

In the illustrated example, a new state estimate is generated (block235-6). This may be done using any optimisation method known in the art,for example by gradient descent or by a Newtonian method.

The validated predicted state is used to estimate the next state in thepredicted aircraft trajectory (block 235-7), and the example method 700returns to block 235-4.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

What is claimed is:
 1. An apparatus comprising: an aircraft intentprocessor comprising: an aircraft intent input to receive aircraftintent data representative of aircraft intent instructions; an aircraftstate input to receive state data representative of a state of anaircraft; and a residual output; wherein the aircraft intent processoris to: calculate residual data representative of an error between astate of the aircraft commanded by the aircraft intent data and thestate of the aircraft expressed by the state data, wherein the aircraftintent processor includes an effects manager to calculate the residualdata by: determining an error metric from one of the aircraft intentinstructions represented by the aircraft intent data; and evaluating theerror metric using the state of the aircraft commanded by the receivedaircraft intent data and the state of the aircraft expressed by thereceived state data; and output the residual data via the residualoutput.
 2. The apparatus of claim 1, wherein the aircraft intent inputis to receive aircraft intent data representative of trigger conditionsfor indicating when a corresponding one of the aircraft intentinstructions has been executed, the aircraft intent processor furthercomprising: a trigger manager to determine whether the state datareceived by the aircraft state input fulfils one of the triggerconditions.
 3. The apparatus of claim 1 further comprising: an actuatorto control the flight of the aircraft; a flight control system tocontrol the actuator; and a navigation system to monitor the state ofthe aircraft and provide the state data representative of the state ofthe aircraft to the aircraft state input.
 4. The apparatus of claim 3,wherein the flight control system comprises a controller to output acontrol signal to the actuator based on the residual data received fromthe aircraft intent processor.
 5. The apparatus of claim 1 furthercomprising: a trajectory computation infrastructure having a numericalsolver to: generate the state data based on the residual data output bythe aircraft intent processor; and provide the state data to theaircraft intent processor.
 6. The apparatus of claim 5, wherein thestate data generated by the numerical solver is estimated state data. 7.The apparatus of claim 5 further comprising a tracking system to providepresent location data of the aircraft to the numerical solver.
 8. Theapparatus of claim 7, wherein the numerical solver is to predict abehavior of the aircraft based on the aircraft intent data and thepresent location data.
 9. The apparatus of claim 1, wherein the state ofthe aircraft is defined by six degrees of freedom.
 10. The apparatus ofclaim 1, wherein the aircraft intent data is in the form of aircraftintent description language.
 11. A system comprising: an aircraft havingan actuator and a first aircraft intent processor; and an air trafficcontrol station to monitor the aircraft, the air traffic control stationhaving a second aircraft intent processor, wherein: aircraft intent datarepresentative of aircraft intent instructions is received by theaircraft and the air traffic control station; the aircraft is to executethe aircraft intent instructions using the first aircraft intentprocessor, the first aircraft intent processor comprising: a firstaircraft intent input to receive the aircraft intent data; a firstaircraft state input to receive first state data representative of afirst state of the aircraft; and a first residual output, wherein thefirst aircraft intent processor is to: calculate first residual datarepresentative of a first error between a state of the aircraftcommanded by the received aircraft intent data and the first state ofthe aircraft expressed by the first state data; and output the firstresidual data via the first residual output; and the air traffic controlstation is to predict the trajectory of the aircraft using the secondaircraft intent processor, the second aircraft intent processorcomprising: a second aircraft intent input to receive the aircraftintent data; a second aircraft state input to receive second state datarepresentative of a second state of the aircraft; and a second residualoutput, wherein the second aircraft intent processor is to: calculatesecond residual data representative of a second error between the stateof the aircraft commanded by the received aircraft intent data and thesecond state of the aircraft expressed by the second state data; andoutput the second residual data via the second residual output.
 12. Thesystem of claim 11, wherein the aircraft further comprises: a flightcontrol system to control the actuator; a navigation system to monitorthe first state of the aircraft and provide the first state datarepresentative of the first state of the aircraft to the first aircraftstate input; and a controller to output a control signal to the actuatorbased on the first residual data.
 13. The system of claim 11, whereinthe air traffic control station comprises: a trajectory computationinfrastructure; and a numerical solver to generate the second state databased on the second residual output from the second aircraft intentprocessor, and to provide the second state data to the second aircraftintent processor.